MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models
Authors: Mahdi Imani, Seyede Fatemeh Ghoreishi, Douglas Allaire, Ulisses M. Braga-Neto7858-7865
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The accuracy and speed of the algorithm are demonstrated by numerical experiments using synthetic gene expression data from a gene regulatory network model and real data from the VIX stock price index. |
| Researcher Affiliation | Academia | Mahdi Imani Texas A&M University m.imani88@tamu.edu Seyede Fatemeh Ghoreishi Texas A&M University f.ghoreishi88@tamu.edu Douglas Allaire Texas A&M University dallaire@tamu.edu Ulisses M. Braga-Neto Texas A&M University ulisses@ece.tamu.edu |
| Pseudocode | Yes | Algorithm 1 MFBO-SSM Algorithm |
| Open Source Code | No | The paper does not provide an explicit statement or link to open-source code for the methodology. |
| Open Datasets | No | The paper mentions using |
| Dataset Splits | No | The paper describes data generation and lengths (e.g., |
| Hardware Specification | Yes | All experiments have been conducted on a PC with an Intel Core i7-4790 CPU@3.60-GHz clock and 16 GB of RAM. |
| Software Dependencies | No | The paper does not specify software names with version numbers for its dependencies. |
| Experiment Setup | Yes | MFBO-SSM algorithm uses N1 = 100, N2 = 1000, N3 = 5000, corresponding to small, medium, and large particle sample sizes. Other methods use a fixed particle sample size N = 1000. [...] We are interested in estimating the true parameter θ = (σ , φ , β , µ ) = (0.97, 0.55, 0.95, 0.1) from synthetic data, where Θ = [0, 2] [ 1, 1] [0, 10] [0, 5]. [...] The MFBO-SSM, BO, EM, and ML algorithms all stop when the change in the estimated value of all parameters over a window of length 20 falls bellow 5% of their range, whereas the PMMH algorithm continues over a fixed number of 6,000 iterations. |